The Mathematics of AI Uncertainty
Professor of Information Engineering; VP of Research
44:42·2026·graduate level·Public Colloquium
Explore the foundational mathematical principles underpinning AI uncertainty, from historical perspectives to contemporary Bayesian approaches in machine learning and large language models.
Long before the current wave of large language models, one academic researcher was trying to give machines a sense of their own limitations. Zoubin Ghahramani has spent the last 30 years pioneering a type of intelligence built on the mathematics of uncertainty. Today, as a professor at Cambridge and VP of research at Google DeepMind, Zoubin finds himself at the heart of an interesting debate: will improving machine uncertainty be one of the missing pieces to ever improving AI?
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